Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
Article Fingerprint
ReserarchID
C: FINANCE1YQ76
In our paper, we investigate the explanatory power to the crypto currency return premium of market factor and size factor. We tested both the value-weighted and the equally weighted market factor and a big minus small Fama-French size factor. We found the market and size together can explain 33% of the premium. We also used UMAP to find a non-linear transformation of the crypto returns to create two factors, who can explain over 80% of the premium in both training and testing periods. However, further analysis and research needs to be carried out to decipher what these two factors represent.
Saket Kumar. 2020. \u201cFactor Model in Cryptocurrency Market\u201d. Global Journal of Management and Business Research - C: Finance GJMBR-C Volume 20 (GJMBR Volume 20 Issue C3): .
Crossref Journal DOI 10.17406/GJMBR
Print ISSN 0975-5853
e-ISSN 2249-4588
The methods for personal identification and authentication are no exception.
The methods for personal identification and authentication are no exception.
Total Score: 103
Country: India
Subject: Global Journal of Management and Business Research - C: Finance
Authors: Saket Kumar, Mike Zeng, Ruinan Lu (PhD/Dr. count: 0)
View Count (all-time): 116
Total Views (Real + Logic): 2312
Total Downloads (simulated): 1142
Publish Date: 2020 07, Fri
Monthly Totals (Real + Logic):
Neural Networks and Rules-based Systems used to Find Rational and
A Comparative Study of the Effeect of Promotion on Employee
The Problem Managing Bicycling Mobility in Latin American Cities: Ciclovias
Impact of Capillarity-Induced Rising Damp on the Energy Performance of
In our paper, we investigate the explanatory power to the crypto currency return premium of market factor and size factor. We tested both the value-weighted and the equally weighted market factor and a big minus small Fama-French size factor. We found the market and size together can explain 33% of the premium. We also used UMAP to find a non-linear transformation of the crypto returns to create two factors, who can explain over 80% of the premium in both training and testing periods. However, further analysis and research needs to be carried out to decipher what these two factors represent.
We are currently updating this article page for a better experience.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.